The Use of Multi-Scale Fiducial Markers To Aid Takeoff and Landing Navigation by Rotorcraft
This work addresses navigation challenges for rotorcraft during critical phases like takeoff and landing, but it is incremental as it extends prior marker-based methods to nested layouts.
This paper tackles the problem of reliable takeoff and landing navigation for rotorcraft by evaluating visual SLAM enhanced with multi-scale fiducial markers, showing improved performance in various environmental conditions with metrics like absolute trajectory error and pose estimation coverage.
This paper quantifies the performance of visual SLAM that leverages multi-scale fiducial markers (i.e., artificial landmarks that can be detected at a wide range of distances) to show its potential for reliable takeoff and landing navigation in rotorcraft. Prior work has shown that square markers with a black-and-white pattern of grid cells can be used to improve the performance of visual SLAM with color cameras. We extend this prior work to allow nested marker layouts. We evaluate performance during semi-autonomous takeoff and landing operations in a variety of environmental conditions by a DJI Matrice 300 RTK rotorcraft with two FLIR Blackfly color cameras, using RTK GNSS to obtain ground truth pose estimates. Performance measures include absolute trajectory error and the fraction of the number of estimated poses to the total frame. We release all of our results -- our dataset and the code of the implementation of the visual SLAM with fiducial markers -- to the public as open-source.